Social Support. Characterizing audience engagement around self-disclosure comments in their content, we identify supportive comments according to the four major classes of social support around health concerns—prescriptive, informational, instrumental, and emotional support—from established literature [1]}, [2]}, [3]} and label the main type of support each comment falls under. We then fit logistic regression models on the dependent variable of receipt, aiming to identify where users are more likely to receive a supportive comment in response to disclosure; including song features as independent variables and song popularity, comment length, user demographics, and comment LDA topic distributions as controls.
We observe that emotional (52%, e.g., “UTF8gbsn加油，事情一定会好起来的我保证”, meaning “good luck, everything will be better I promise”) and prescriptive support (31%, e.g., “UTF8gbsn听一些令人振奋的歌曲吧”, meaning “listen to heart raising songs”) largely exceeds informational (9%, e.g., “UTF8gbsn...治疗可能会有帮助，两年治疗后我...”, meaning “...therapy could help, after two years of therapy I...”) and instrumental (8%, e.g., “UTF8gbsn...你可以私聊我”, meaning “...you can private message me”) forms in response to disclosures.
Several psycholinguistic lyrical features proved statistically significant (p<0.05) in predicting if a disclosure comment to a song would receive a supportive reply; the rate of terms in lyrics relating to social processes, specifically friend (+2.23) and ingest (+0.97), positively predict this prosocial behavior, and negative emotion terms (-2.04) do so negatively, mirroring negative correlations between sadness and prosocial tendencies [4]}. For musical features, only reverberation did so positively (+0.90).
While past work has studied the prosocial effects of music, most have only used a limited set of author-chosen songs [5]}, [6]} or crowd-sourced prosocial perceptions [7]}; here, we specifically identify what makes for prosocial songs and situate our study in the context of social support to mental health self-disclosures.
Taken together, these observations not only provide ample pointers for music therapists on musical and dyadic conversational means for more successful emotion-focused interventions [8]}
but also guide users on how to effectively find social support on the platform when needed [9]}.
